Can I check the total number of contacts in a list using the agent?

Yes! Use the `get_contact_list` tool with the List ID. Your agent will fetch the detailed metadata, which includes the `total_contacts` field for that specific list.

How do I add a new contact to an existing list?

Simply ask the agent to `create_contact` and provide the List ID and the email address. The contact will be added to your Cakemail list instantly.

Does the integration allow creating a new campaign?

Yes. Use the `create_campaign` action and provide the name and subject. Your agent will create the campaign in your Cakemail account, allowing you to finalize the content later.

Cakemail MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Cakemail
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Cakemail through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Cakemail "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Cakemail?"
    )
    print(result.data)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Cakemail MCP Server

Connect your Cakemail account to any AI agent and orchestrate your email marketing, subscriber management, and campaign tracking through natural conversation.

Pydantic AI validates every Cakemail tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

List Oversight — List all your contact lists and retrieve detailed metadata, including total contact counts.
Campaign Management — List all email campaigns and retrieve detailed metadata, including subjects and statuses.
Subscriber Coordination — List contacts within specific lists and add new subscribers directly from your workspace.
Analytics Tracking — Retrieve recent analytics logs to monitor your email performance.
Account Insights — Access your core profile information and account settings straight from your workspace.
Deep Dives — Get detailed data for specific list or campaign IDs using natural language.

The Cakemail MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Cakemail to Pydantic AI via MCP

Follow these steps to integrate the Cakemail MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Cakemail with type-safe schemas

Why Use Pydantic AI with the Cakemail MCP Server

Pydantic AI provides unique advantages when paired with Cakemail through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Cakemail integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Cakemail connection logic from agent behavior for testable, maintainable code

Cakemail + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Cakemail MCP Server delivers measurable value.

Type-safe data pipelines: query Cakemail with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Cakemail tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Cakemail and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Cakemail responses and write comprehensive agent tests

Cakemail MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Cakemail to Pydantic AI via MCP:

create_campaign

Create a new email campaign

create_contact

Add a contact to a list

create_contact_list

Create a new contact list

get_account_info

Retrieve core account information

get_analytics

Retrieve recent analytics logs

get_campaign

Get details of a specific campaign

get_contact_list

Get details of a specific contact list

list_campaigns

List all email campaigns

list_contact_lists

List all contact lists

list_contacts

List contacts in a specific list

Example Prompts for Cakemail in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Cakemail immediately.

"List all my contact lists in Cakemail."

"Show the last 5 email campaigns."

"Add john.doe@example.com to the 'Newsletter' list."

Troubleshooting Cakemail MCP Server with Pydantic AI

Common issues when connecting Cakemail to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Cakemail + Pydantic AI FAQ

Common questions about integrating Cakemail MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Cakemail MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.